Li Yuzhi Z, Johnston Lee J, Dawkins Marian S
West Central Research and Outreach Center, University of Minnesota, Morris, MN 56267, USA.
Department of Zoology, University of Oxford, John Krebs Field Station, Wytham Oxford OX2 8QJ, UK.
Animals (Basel). 2020 Feb 18;10(2):323. doi: 10.3390/ani10020323.
A study was conducted to evaluate activity changes in pigs associated with the development of tail-biting outbreaks using optical flow algorithms. Pigs ( = 120; initial body weight = 25 ± 2.9 kg) housed in four pens of 30 pigs were studied for 13 weeks. Outbreaks of tail biting were registered through daily observations. Behavior of pigs in each pen was video-recorded. Three one-hour video segments, representing morning, noon, and afternoon on days 10, 7, and 3 before and during the first outbreak of tail biting were scanned at 5-min intervals to estimate time budget for lying, standing, eating, drinking, pig-directed behavior, and tail biting. The same video segments were analyzed for optical flow. Mean optical flow was higher three days before and during the tail-biting outbreak, compared to 10 days before the outbreak ( < 0.05), suggesting that pigs may increase their activity three days before tail-biting outbreaks. All optical flow measures (mean, variance, skewness, and kurtosis) were correlated (all < 0.01) with time spent standing, indicating that movement during standing may be associated with optical flow measures. These results suggest that optical flow might be a promising tool for automatically monitoring activity changes to predict tail-biting outbreaks in pigs.
进行了一项研究,以使用光流算法评估与咬尾暴发发展相关的猪的活动变化。将120头猪(初始体重 = 25 ± 2.9千克)饲养在四个猪栏中,每个猪栏30头猪,研究持续13周。通过每日观察记录咬尾暴发情况。对每个猪栏中的猪的行为进行视频记录。在首次咬尾暴发前和暴发期间的第10天、第7天和第3天,以5分钟的间隔扫描代表上午、中午和下午的三个一小时视频片段,以估计躺卧、站立、进食、饮水、指向猪的行为和咬尾的时间分配。对相同的视频片段进行光流分析。与暴发前10天相比,咬尾暴发前三天和暴发期间的平均光流更高(P < 0.05),这表明猪在咬尾暴发前三天可能会增加活动量。所有光流测量值(均值、方差、偏度和峰度)均与站立时间相关(所有P < 0.01),表明站立期间的运动可能与光流测量值有关。这些结果表明,光流可能是自动监测活动变化以预测猪咬尾暴发的一种有前途的工具。